Wesley Dyk

CVQBoost is a new classification algorithm designed to harness QCi’s Dirac-3 entropy-based quantum system for high-dimensional machine learning. In this session, Wes Dyk shares benchmark results from a fraud detection use case, comparing CVQBoost’s performance to XGBoost on advanced GPU infrastructure. The results demonstrate significant runtime advantages and scalability, with CVQBoost maintaining strong accuracy across datasets up to 70 million samples—highlighting its potential for real-world ML tasks in finance and cybersecurity.